% input x: made of K feature row vectors of dimension M
% input d: {-1,1}^K: column vector of dimension K
% output w: (normalized) weight vector the M+1st component theta
% output n_w_changes: number of weight changes
% output n_iter: number of for-loop cycles
% output n_misclassified: dynamics of number of misclassified data

% sphere model test fitness function
% input x: the x value
function [y] = F(x)
	y = norm(x)^2;
endfunction